|
Enrico Cameron, University of Pavia (Italy)
Gian Francesco Peloso, University of Pavia (Italy)
Giorgio Pilla, University of Pavia (Italy)
Gianfranco Ciancetti, University of Pavia (Italy)
Luca Garavaglia, University of Pavia (Italy)
|
|
To protect groundwater resources is important to assess and manage pollution risk. The uncertainties affecting the quantitative assessment of risk, for example those regarding aquifer's vulnerability, normally imply that risk can take more than one possible value within a given range; selecting pollution prevention measures disregarding uncertainty may lead to underestimating risk itself and, therefore, to insufficient pollution prevention actions. When environmental risks cannot be exactly estimated the precautionary principle should be applied. This work illustrates a method for applying such principle to the management of groundwater pollution risk, with the aim of reducing the likelihood of underestimating risk and formulating inadequate pollution prevention policies.
As an example the method is applied to the assessment of groundwater pollution risk caused by nitrates coming from agricultural activities. Risk is calculated as the product of a hazard index obtained through the IPNOA model (Padovani, Trevisan and Capri, 2000, Padovani and Trevisan, 2002) and a vulnerability index estimated with the rating system SINTACS R5 (Civita, De Maio, 1997) for the territory of Vigevano (Italy). The procedure employs possibility theory and fuzzy mathematics: 1) for defining quantitative models of the uncertainties as to the variables used in risk assessment, including those of a subjective nature; 2) for propagating such uncertainties to the final estimated risk value; 3) for calculating how effective, from the point of view of precaution, are different pollution prevention policies regulating the agricultural activities producing nitrates, starting from the quantitative definition of a precaution degree that can be associated to each policy.
The work - which follows previous ones - also describes how to automatically obtain risk maps corresponding to different precaution degrees and how an optimal precaution degree, and the correspondent policy, may be selected.
|
